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The kinetics of immunoglobulin G (IgG) avidity maturation during severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection obtained from 217 participants of the Ischgl cohort, Austria, was studied 0.5–1.5 months (baseline) and 7–8 months (follow-up) after infection. The IgG avidity assay, using a modified IgG enzyme-linked immunosorbent assay (ELISA) and 5.5 M urea, revealed that old age does not diminish the increase in avidity, detected in all participants positive at both time points, from 18% to 42%. High avidity was associated with a marked residual neutralization capacity in 97.2.% of participants (211/217), which was even higher in the older age group, revealing an important role of avidity assays as easy and cheap surrogate tests for assessing the maturation of the immune system conveying potential protection against further SARS-CoV-2 infections without necessitating expensive and laborious neutralization assays.

Background In early March 2020, a SARS-CoV-2 outbreak in the ski resort Ischgl in Austria triggered the spread of SARS-CoV-2 throughout Austria and Northern Europe. In a previous study, we found that the seroprevalence in the adult population of Ischgl had reached 45% by the end of April, representing an exceptionally high level of local seropositivity in Europe. We performed a follow-up study in Ischgl, which is the first to show persistence of immunity and protection against SARS-CoV-2 and some of its variants at a community level. Methods Of the 1259 adults that participated in the baseline study, 801 have been included in the follow-up in November 2020. The study involved the analysis of binding and neutralizing antibodies and T cell responses. In addition, the incidence of SARS-CoV-2 and its variants in Ischgl was compared to the incidence in similar municipalities in Tyrol until April 2021. Findings For the 801 individuals that participated in both studies, the seroprevalence declined from 51.4% (95% confidence interval (CI) 47.9-54.9) to 45.4% (95% CI 42.0-49.0). Median antibody concentrations dropped considerably (5.345, 95% CI 4.833 - 6.123 to 2.298, 95% CI 2.141 - 2.527) but antibody avidity increased (17.02, 95% CI 16.49 - 17.94 to 42.46, 95% CI 41.06 - 46.26). Only one person had lost detectable antibodies and T cell responses. In parallel to this persistent immunity, we observed that Ischgl was relatively spared, compared to similar municipalities, from the prominent second COVID-19 wave that hit Austria in November 2020. In addition, we used sequencing data to show that the local immunity acquired from wild-type infections also helped to curb infections from variants of SARS-CoV-2 which spread in Austria since January 2021. Interpretation The relatively high level of seroprevalence (40-45%) in Ischgl persisted and might have been associated with the observed protection of Ischgl residents against virus infection during the second COVID-19 wave as well as against variant spread in 2021. Funding Funding was provided by the government of Tyrol and the FWF Austrian Science Fund.

BackgroundIn early March 2020, a SARS-CoV-2 outbreak in the ski resort Ischgl in Austria initiated the spread of SARS-CoV-2 throughout Austria and Northern Europe. In a cross-sectional study, we found that the seroprevalence in the adult population of Ischgl had reached 45% by the end of April. To answer the question of how long immunity persists and what effect this high-level immunity had on virus transmission, we performed a follow-up study in early November, 2020.MethodsOf the 1259 adults that participated in the baseline study, 801 could be included in the follow-up. The study involved the analysis of binding and neutralizing antibodies and T cell responses. In addition, the incidence of SARS-CoV-2 infections in Ischgl was compared to the incidence in similar municipalities in Tyrol throughout 2020.FindingsFor the 801 individuals that participated in both studies, the seroprevalence declined from 51.4% (95% confidence interval (CI) 47.9 - 54.9) to 45.4% (95% CI 42.0 - 49.0). Median antibody concentrations dropped considerably but antibody avidity increased. T cell responses were analysed in 93 cases, including all 4 formerly seropositive cases that had lost antibodies in all assays, three of which still had detectable T cell memory. In addition, the incidence in the second COVID-19 wave that hit Austria in November 2020, was significantly lower in Ischgl than in comparable municipalities in Tyrol or the rest of Austria.InterpretationThis study has important implications as it shows that although antibodies to SARS-CoV-2 declined, T and B cell memory can be detected for up to 8 months. Complemented by infection prevention measures a level of around 40-45% immunity in Ischgl significantly reduced local virus transmission during the second wave in Austria in November 2020.FundingFunding was provided by the government of Tyrol and the FWF Austrian Science Fund.

Die Durchführung von manuellen Ertragsschätzungen ist meist mit einem hohen Arbeitsaufwand und hohen Kosten verbunden. Mithilfe von modernen Bilderkennungssystemen ist es bereits möglich Ertragsprognosen zu erstellen, um flächenbezogene Ertragsleistung und die Fruchtgrößenverteilung zu ermitteln. Dadurch können Kulturmaßnahmen zielgerichteter eingesetzt und die Lagerung sowie die Logistik optimiert werden. Deshalb wurden in dieser Arbeit-fünf verschiedene kommerziell erhältliche Systeme auf ihre Genauigkeit und Praxistauglichkeit bei verschiedenen Sorten und auf verschiedenen Standorten getestet. Dafür wurden die erhaltenen Daten mit manuell ermittelten Daten verglichen und die Abweichung berechnet. Dabei wurde festgestellt, dass große Unterschiede zwischen den verschiedenen Systemen vorlagen, wobei einige Systeme bereits eine ausreichende Genauigkeit aufwiesen. Beim Großteil der Systeme waren jedoch zu große Abweichungen vorhanden und dafür aufgebrachte Zeitaufwand für die Erfassung der Daten lag häufig über dem der manuellen Messung.

Die Regulierung des vegetativen Wachstums im Apfelanbau ist eine wichtige Maßnahme, um den Ertrag konstant zu halten und die Fruchtqualität zu fördern. In zwei verschiedenen Versuchen wurden am Versuchszentrum Laimburg unterschiedliche Methoden zur Wachstumsregulierung untersucht. Unter anderem wurde das Handelsprodukt Paclot New mit dem Wirkstoff Paclobutrazol, früher bekannt unter dem Handelsnamen Cultar getestet. Trotz positiver Ergebnisse bei älteren Versuchen, konnte bei beiden Versuchen kein wachstumsregulierender Effekt von Paclobutrazol festgestellt werden. Behandlungen mit dem Wirkstoff Prohexadion-Ca wiesen hingegen eine signifikante Reduktion des Triebwachstums im Vergleich zur unbehandelten Kontrolle auf. Der Wurzelschnitt und Behandlungen mit Paclobutrazol verkleinerten die Fruchtgröße in machen Versuchsjahren signifikant. Rückstände von Paclobutrazol konnten während des Versuchs, außer in den Blättern und Trieben und ein Jahr im Boden nicht festgestellt werden.

Patients with advanced Parkinson’s disease regularly experience unstable motor states. Objective and reliable monitoring of these fluctuations is an unmet need. We used deep learning to classify motion data from a single wrist-worn IMU sensor recording in unscripted environments. For validation purposes, patients were accompanied by a movement disorder expert, and their motor state was passively evaluated every minute. We acquired a dataset of 8,661 minutes of IMU data from 30 patients, with annotations about the motor state (OFF,ON, DYSKINETIC) based on MDS-UPDRS global bradykinesia item and the AIMS upper limb dyskinesia item. Using a 1-minute window size as an input for a convolutional neural network trained on data from a subset of patients, we achieved a three-class balanced accuracy of 0.654 on data from previously unseen subjects. This corresponds to detecting the OFF, ON, or DYSKINETIC motor state at a sensitivity/specificity of 0.64/0.89, 0.67/0.67 and 0.64/0.89, respectively. On average, the model outputs were highly correlated with the annotation on a per subject scale (r = 0.83/0.84; p

The assessment of Parkinson's disease (PD) poses a significant challenge as it is influenced by various factors which lead to a complex and fluctuating symptom manifestation. Thus, a frequent and objective PD assessment is highly valuable for effective health management of people with Parkinson's disease (PwP). Here, we propose a method for monitoring PwP by stochastically modeling the relationships between their wrist movements during unscripted daily activities and corresponding annotations about clinical displays of movement abnormalities. We approach the estimation of PD motor signs by independently modeling and hierarchically stacking Gaussian process models for three classes of commonly observed movement abnormalities in PwP including tremor, (non-tremulous) bradykinesia, and (non-tremulous) dyskinesia. We use clinically adopted severity measures as annotations for training the models, thus allowing our multi-layer Gaussian process prediction models to estimate not only their presence but also their severities. The experimental validation of our approach demonstrates strong agreement of the model predictions with these PD annotations. Our results show the proposed method produces promising results in objective monitoring of movement abnormalities of PD in the presence of arbitrary and unknown voluntary motions, and makes an important step towards continuous monitoring of PD in the home environment.

The number of aged population is growing consistently, and is expected to triple by few next decades. One of the most threatening risk aged population have to face in their daily life is falling. Falling can pose serious injuries and consequences to elderly people, especially when they live alone or have cognitive dysfunction. If the elderly lives alone when an accident happens, it is more likely to take a long time until someone notices and provides rescue. Moreover, if the elderly has cognitive disorder such as Alzheimer’s disease, it is possible that he or she will not try to seek help. In this paper, an online platform called WECARE is proposed. WECARE aims to minimize the consequence of delayed rescue after a fall accident. The main advantage of the platform is the integration of community volunteers into the already widespread technologies such as fall detection systems and automatic doors. The benefits of volunteers could be a faster response after a fall accident and social connection provided to elderly people, especially the ones who live alone. This paper also describes how the idea was originated, modified, and improved through methodology. It also discusses advantages of the platform, limitations, as well as its future.